The Technical And Management Challenges At Big Data Analysis Essay

The analysis of big data is the process of organizing, collection, analyze and examining the large volume of data to find patterns, market trends and useful information. This analysis helps organizations to better understanding about the information within data, and helps analyst to make better

The authors of [1] aim to dispel some of the current hype surrounding big data, mainly the misnomer that it is all about technology and the process is automated. In fact there are three critical elements requiring human expertise 1) the data must be the right kind, of sufficient quantity, and clean 2) a specific process must be followed for success starting with the identification of the objective 3) expert humans who know how to use the technology, execute the big data process, and perform the mining tasks which require significant mathematical calculations.

Big Data is an expansive phrase for data sets so called big, large or complex that they are very difficult to process using traditional data processing applications. Challenges include analysis, capture, curation, search, sharing, storage, transfer, visualization, and information privacy. In common usage, the term big data has largely come to refer simply to the use of predictive analytics. Big data is a set of techniques and technologies that need or require new forms of integration to expose large invisible values from large datasets that are diverse, complex, and of a massive scale. When big data is effectively and efficiently captured, processed, and analyzed, companies

The author points out that although there are existing algorithms and tools available to handle Big Data, they are not sufficient as the volume of data is exponentially increasing every day. To show the usefulness of Big Data mining, the author highlighted the work done by United Nations. In order to further enhance the reader’s perspective, the author provided research work of various professionals to educate its readers about the most recent updates in Big Data mining field. The author further describes the controversies surrounding Big Data. The author has first provided the context and exigence by elaborating on why we need new algorithm and tools to explore the Big Data. The author used the strategy of highlighting the logos by mentioning the research work of different industry professionals, workshops conducted on Big Data and was able to appeal to connect to the reader’s ethos. The author also used pathos by urging the budding Big Data researchers to further dig deep into the topic and explore this area

The emergence of big data has provided different avenues for organizations to use data to improve different aspects of their respective operations. Be it customer service, research and development, or market position, Big Data has the potential to be a significant driving force in all these areas. However, there’s still a significant gap between the ability of Big Data to produce insightful analytical information based on real-time data and the ability of organizations to capture and utilize this readily available tool. This is, in part, due to the fact that the systems and processes necessary to fully maximize the usefulness of Big Data is currently lacking in most organizations. This lack of a conducive habitat for Big Data is further magnified in new organizations without any knowledge of Big Data. For organizations that have that have little to no knowledge of Big Data, there must be a thorough assessment of the benefits of big data and how they could improve the organizations overall place in the market. There also needs to be steps taken towards the design of frameworks that will enable the organization to better capture and utilize Big Data.

This article reviews the application of big data and big data analysis at Facebook. As explained above, social networking sites such as Facebook generate terabytes of information on a daily basis and thus have the opportunity of generating massive amounts of knowledge from these data. The article has been divided into five chapters including the introduction, a brief description into Facebook, the big data strategies at Facebook, the big data technologies at the company to support strategic operations and the implementation of the big data strategies at the company. The paper then concludes with a brief conclusion briefing on the findings and the results of the discussion.

In a fast paced, business ordinated technological world the overall welfare of a company is tied to the success or failure to make the tough decisions. On one instance a company’s CEO might be able to make the choices based on experience, advice, or simple gut instinct. However, this is not the only skill one needs. There is a great deal of information to be found in being able to see investments in data and analytics. These decisions are based off of big data. Big data is a catch-phrase, used to describe a massive volume of both structured and unstructured data that is too large to process using traditional database and software techniques. The volume of data is in most cases is too big, moves too fast or it exceed the processing capacity the company has. Despite these potential drawbacks, big data contains the potential to help companies by improving operations and making faster, more intelligent decisions. This can be broken into three key parts, knowledge, data, and information.

Business thrive when they have the most accurate, up-to-date, and relevant information at their disposal. This information can be used for a plethora of pertinent markers in small and large businesses, relating to accounting, investments, consumer activity, and much more. Big data is a term used to describe the extremely large amounts of data that floods a business every day. For decades, big data has been a growing field, facing controversy on many levels, but as of late, it has been a major innovator in the challenge of making businesses more sustainable. Big data is often scrutinized for its over-generalization and inability to display meaningful results at times. When applied correctly, data analysis can bring earth-altering information to the table.

Big data is buzzword in every field of business as well as research. Organizations have found its application across various sectors from Sports to Security, from Healthcare to e-Commerce.

Big Data Analytics is the process of analyzing large amounts of raw information generated and stored. In today 's fast paced technologies, we are inundated with in a tsunami of data before us. All applications, in a broader range are depending on data in a remarkable way. BDA is driving almost every field in our society from Retail, Manufacturing and Mobile applications to life and physical sciences. The Data Analytics techniques are performed to uncover hidden patterns, unknown correlations and other useful information. Earlier, Data Analytics were based on guessing and inaccurate data models but currently this can be done directly. Big Data has truly revolutionized scientific research (Computing Research Association 2014).

The industry is inundated with articles on big data. Big data news is no longer confined to the technical web pages. You can read about big data in the mainstream business publications such as Forbes and The Economist. Each week the media reports on breakthroughs, startups, funding and customer use cases. No matter your source for information on big data, one thing they all have in common is that the amount of information an organization will manage is only going to increase; this is what’s driving the ‘big data’ movement.

The guarantee of information driven choice making is presently being perceived extensively, and there is developing excitement for the thought of ``Big Data. ' ' While the guarantee of Big Data is genuine for instance, it is assessed that Google alone contributed 54 billion dollars to the US economy in 2009 - there is right now a wide crevice between its potential and its acknowledgment. Heterogeneity, scale, convenience, intricacy, and protection issues with Big Data block progress at all periods of the pipeline that can make esteem from information. The estimation of information blasts when it can be connected with other information, subsequently information combination is a noteworthy maker of quality. Since most information is directly produced in advance today, we have the open door and the test both to impact the creation to encourage later linkage and to naturally interface already made information. We trust that fitting interest in Big Data will prompt another rush of central mechanical advances that will be epitomized in the following eras of Big Data administration and investigation stages, items, and frameworks. The interest in Big Data, legitimately coordinated, can result in major investigative advances, as well as establish the framework for the up and coming era of advances in science, solution, and business.

Big data is an extensive collection of structured and unstructured data. It is a modern day technology which is applied to store, manage and analyze data that are not possible to manage, store and analyze by using the commonly used software or tools. Since all of our daily tasks are overtaken by the modern technologies and all the businesses and organizations are using internet system to operate, the production of data has increased significantly in past

Data itself is useless, until it is mined and transformed into a valuable source of knowledge discovery. Due to its conversion into useful information, data mining has become the leading source being used in many fields worldwide. “Data mining is based on complex algorithms that allow for the segmentation of data to identify patterns and trends, detect anomalies, and predict the probability of various situational outcomes.”[1] Many organizations from healthcare to multimedia and more are relaying on data and getting developed through the use of it. Regardless of how, data warehouse changed its rhythm and dimension in terms of measurements such as: variety, volume and velocity. Today, one can see the current trends of data mining in different fields such as social networks, healthcare and businesses. As data mining is giving the opportunity for those fields to get advanced, "Big Data" is also opening up new doors within itself as the new trends emerge.

The emerging data from the everywhere in the world make the birth of big data era. There exist potential values in those data, while the big volume, variety and velocity [2] of the data make it nearly impossible for humans to analyze resources manually so as to find the hidden treasures. Under this circumstance, the concept and technique